Information Retrieval Activities Research Articles

Strengthening the search for information for homemakers in situations of information overload

Information retrieval in a vital information retrieval system process learned by homemakers. Especially information relating to households. The service method implemented uses strengthening information retrieval based on interview results. The results of the interviews illustrate that the retrieval system is a series of system processes in carrying out information retrieval activities until documents or information are found based on queries so that they can meet user needs and satisfy requests for information from users. The steps in carrying out information search activities, namely: starting, chaining, browsing, differentiating, monitoring, extracting, verifying, and ending. Then to become community information, the community must be able to make changes. For example, there is progress in information, one of which is in the field of education. Strengthening is done by strengthening people's behavior towards information-seeking ways to avoid hoaxing information during an information overload.

LaSER: Language-specific event recommendation

While societal events often impact people worldwide, a significant fraction of events has a local focus that primarily affects specific language communities. Examples include national elections, the development of the Coronavirus pandemic in different countries, and local film festivals such as the César Awards in France and the Moscow International Film Festival in Russia. However, existing entity recommendation approaches do not sufficiently address the language context of recommendation. This article introduces the novel task of language-specific event recommendation, which aims to recommend events relevant to the user query in the language-specific context. This task can support essential information retrieval activities, including web navigation and exploratory search, considering the language context of user information needs. We propose LaSER, a novel approach toward language-specific event recommendation. LaSER blends the language-specific latent representations (embeddings) of entities and events and spatio-temporal event features in a learning to rank model. This model is trained on publicly available Wikipedia Clickstream data. The results of our user study demonstrate that LaSER outperforms state-of-the-art recommendation baselines by up to 33 percentage points in MAP@5 concerning the language-specific relevance of recommended events.

Federate learning on Web browsing data with statically and machine learning technique

Purpose Federation analytics approaches are a present area of study that has already progressed beyond the analysis of metrics and counts. It is possible to acquire aggregated information about on-device data by training machine learning models using federated learning techniques without any of the raw data ever having to leave the devices in the issue. Web browser forensics research has been focused on individual Web browsers or architectural analysis of specific log files rather than on broad topics. This paper aims to propose major tools used for Web browser analysis. Design/methodology/approach Each kind of Web browser has its own unique set of features. This allows the user to choose their preferred browsers or to check out many browsers at once. If a forensic examiner has access to just one Web browser's log files, he/she makes it difficult to determine which sites a person has visited. The agent must thus be capable of analyzing all currently available Web browsers on a single workstation and doing an integrated study of various Web browsers. Findings Federated learning has emerged as a training paradigm in such settings. Web browser forensics research in general has focused on certain browsers or the computational modeling of specific log files. Internet users engage in a wide range of activities using an internet browser, such as searching for information and sending e-mails. Originality/value It is also essential that the investigator have access to user activity when conducting an inquiry. This data, which may be used to assess information retrieval activities, is very critical. In this paper, the authors purposed a major tool used for Web browser analysis. This study's proposed algorithm is capable of protecting data privacy effectively in real-world experiments.

PEMANFAATAN SLIMS DALAM SISTEM KATALOGISASI DI RUMAH BACA ANAK NAGARI DAERAH BUKITTINGGI

The impact of technology and internet became the background for the establishment of Rumah Baca Anak Nagari, as well as a component of knowledge management support at RBAN in processing library materials. RBAN used SLiMS as a processing collection system on cataloging and information retrieval activities. This study aims to determine the extent/existence the use of SLiMS application in cataloging system at Rumah Baca Anak Nagari, and the steps of how to operate those application system. This research uses descriptive qualitative research as its method. The findings describe the use of SLiMS application in RBAN is with applying the bibliography feature for the library materials cataloging activity, which produce catalogs and call number labels to facilitate RBAN staff in finding library materials. The operation of SLiMS on the bibliography menu goes through some stages of filling in bibliography descriptions and subject analysis, based on the ISBD bibliography description standard and the DDC classification scheme. It can be concluded that the use of the SLiMS application in RBAN on the bibliography menu runs quite optimally, but has not run optimally in another menu such as membership and circulation features.

INFORMATION RETRIEVAL THROUGH MOODLE (LEARNING MANAGEMENT SYSTEM) AND FACEBOOK (SOCIAL MEDIA) AMONGST STUDENTS OF THE NATIONAL DEFENCE UNIVERSITY OF MALAYSIA (NDUM

In higher education level of study, students often face difficulties in retrieving information especially academic information. In today’s modern world, it is found that there are many ways to retrieve information such as through Moodle, which is a Learning Management System and Facebook, which is a Social Media. The objectives of this study are to identify the preference between retrieving information through Moodle and Facebook, to investigate the reasons why students choose Moodle or Facebook and, to find whether there is correlation between the use of Moodle and Facebook in information retrieval activities. This study uses a quantitative approach where a questionnaire was constructed using Google Form. The sampling used in the study is a convenient sampling which focuses on students from five faculties at the National Defence University of Malaysia, in which questionnaires are distributed to 150 respondents. The data from the questionnaire are analysed using descriptive analysis, reliability analysis, inferential analysis, and thematic analysis. Descriptive analysis is conducted to collect the frequency, percentage, and mean values of data. The reliability analysis is conducted to six questions on Moodle and six questions on Facebook, inferential analysis is conducted to the Dependent Variable and Independent Variables of study questions, and lastly, thematic analysis is conducted to analyse the answers to the open-ended questions. The finding of the study exposed that most students preferred to use the Moodle in retrieving academic information where they claimed, it is a better platform to retrieve information as it has the features which are suitable and seen by the students as a more valid and reliable source of receiving academic information. Nevertheless, there is a fair percentage of students who preferred Facebook over Moodle. This implies that the disparity of students’ preferences in retrieving information should be taken into consideration by educationists when preparing teaching and learning.

Considering the Question of the interoperability

This article concerns the path taken during my scientific research related to the construction and management of digital assets for the design, development, and management of databases, within the scope of the INET-md in Portugal. Its general objective is to facilitate the interoperability, Web dissemination, search, and retrieval of the INET-md's digital collections. This investigation aims to reinforce the alliance between the areas of Information Science and Computer Science. From the Information Science, it brings the applications used for organization,management, and publication of digital assets collections on the Web; and from the Computer Science, it brings syntactic concepts (metadata and protocols) to communicate and exchange data and semantic concepts (ontologies and semantic annotations) to describe data. Both types of concepts can promote interoperability between distinct digital repositories and platforms, providing improvements in information search and retrieval activities.

Exploring intrinsic information content models for addressing the issues of traditional semantic measures to evaluate verb similarity

Semantic similarity measures play an important role in many natural language processing and information retrieval activities. It is highly challenging to measure semantic similarity with higher accuracy. A notable branch of semantic similarity evaluation based on information content (IC) is popular in this aspect. Intrinsic information content (IIC) models are another wing of IC based evaluation. Both IC based and IIC based approaches majorly handled similarity evaluation of nouns. Research related to semantic similarity assessment of verb pairs are rarely discussed. To bridge this gap, this work examines various IC based, IIC based approaches on verb pairs. A detailed discussion of the existing measures and their drawbacks are mentioned in this work. Strategies based on information content, length and depth of the concepts are discussed and tested on benchmark datasets. Existing intrinsic information content models are enhanced by addressing various issues like (a) dealing concepts with no path in WordNet and (b) handling the synonym sets of verb concepts. Measures based on path length, intrinsic information content, combined strategies and non-linear strategies for verb pairs are thoroughly inspected. This paper also presents novel strategies to understand novel aspects that are not addressed before. The strategies are experimented by generating the synonym sets of required parts-of-speech which proved very effective in improving the correlation with human judgment. Results on benchmark datasets specify that the proposed approaches for verb similarity will be a guiding factor for understanding the natural language processing tasks.

The Information Retrieval Competencies of Students Faced with Remote and Blended Teaching

The article describes the problems and features of information retrieval activity of students amid the extreme transition of universities to remote education. The results of a student survey are described, allowing to gain some initial insights into the information retrieval competencies of students in a new reality, when the only opportunity for them is remote access to electronic information systems and electronic educational resources. The competencies necessary for effective information retrieval in a remote and blended teaching have been listed and characterized.

Preferensi penggunaan sumber informasi oleh mahasiswa dalam menyelesaikan tugas kuliah

A wide range of information sources is available to students in various forms providing opportunities for students to utilize these information sources for study purposes. However, studies on the extent to which students know and use it to complete lecture assignments are still rare. This study aimed to identify undergraduate students' experience at one faculty in a university in Semarang when exploring various kinds of information resources to do their assignments. This qualitative study used interviews as the only technique in obtaining data. By employing purposive sampling method, eleven undergraduate students who met the specific criteria participated in this study. All the participants were interviewed using a semi-structured interview. The data were then analyzed by using thematic analysis, to uncover the undergraduate students’ information sources preference and how they used them. The findings revealed students’ selections of information sources for conducting their information retrieval process. They also identified the complexity of student information retrieval activities that were heavily affected by external factors such as the type of assignment, and internal from the students themselves, for example, knowledge of available information sources and motivation to use them. The findings provided evidence to inform the development of library services and information literacy responses to enhance undergraduate students learning.

Standard Operating Procedure Preservasi Koleksi di Perpustakaan (Studi Kasus di Perpustakaan Universitas Sarjanawiyata Tamansiswa Yogyakarta)

Implementation of information retrieval activities in a library is inseparable from the work role of the librarian, for that in a library there needs to be a written policy regarding standard operating procedures for preservation of collections in the library. This research traced information based on standard library procedures regarding collection development policies based on legal standards or preservation SOP policies, with qualitative research methods with the Snowball Sampling technique. The results of this study indicate that in the UST library has not implemented standard operating procedures in preservation collection activities, this is reflected in the process of preservation activities do not have a preservation SOP that is based on the legal basis for preservation of the collection as stated in the SOP document control contained in SOP No. 001.002 / ot 01 01 / isn 6, Law Number 13 of 2018 concerning transfer of printed and recorded works, Regulation of the Head of the National Library Number 16 of 2014 concerning procedures for storing and using special collections and SNI 7330: 2009 for Higher Education libraries .

Using Information Retrieval Activities to Foster Analytical Thinking Skills in Higher Education in Thailand: A Case Study of Local Wisdom Education

Three information retrieving lessons were designed to foster analytical thinking in freshmen with minimal prior active learning experience. Thailand Local Wisdom contents were used as an online information platform due to the scarcity in well-established credible information sources. The lessons were collaborative learning both within own group and between groups. The information retrieving, credibility sorting, classroom sharing, analytical thinking assessments, and self-evaluating activities were conducted in sequential steps and repeated in three trials. A reflective pause was introduced between trials. The self-evaluating pause procedure using teacher’s feedback was possibly a major reason for gains, from 65.0% to 82.5% and to 92.5%, in the number of students exhibiting analytical thinking evidence. A free-response survey after the learning experience showed that the students express high appreciation for the active learning activities as fun and analytical-thinking-promoting learning experiences.

Proactive Information Retrieval by Capturing Search Intent from Primary Task Context

A significant fraction of information searches are motivated by the user’s primary task . An ideal search engine would be able to use information captured from the primary task to proactively retrieve useful information. Previous work has shown that many information retrieval activities depend on the primary task in which the retrieved information is to be used, but fairly little research has been focusing on methods that automatically learn the informational intents from the primary task context. We study how the implicit primary task context can be used to model the user’s search intent and to proactively retrieve relevant and useful information. Data comprising of logs from a user study, in which users are writing an essay, demonstrate that users’ search intents can be captured from the task and relevant and useful information can be proactively retrieved. Data from simulations with several datasets of different complexity show that the proposed approach of using primary task context generalizes to a variety of data. Our findings have implications for the design of proactive search systems that can infer users’ search intent implicitly by monitoring users’ primary task activities.

Keputusan pemustaka dalam penelusuran informasi di Perpustakaan Balai Penelitian Tanaman Rempah dan Obat

The needs of library information need to be met to complete the information needs of the library users who generally have a variety of reasons to perform activities in accordance with their purpose. Information retrieval activity is one of the main activities of the library users at the library of the Research Institute for Spices and Medicinal Herbs (RISMH) to find the source of literature through the Online Public Access Catalog (OPAC) facility. The purpose of the research was to determine the decision of the user in searching for information. The study was conducted from November to December 2017, with materials obtained from the library literature search 2015 -2017 results form. The study used the quantitative descriptive method, while the observed variables were: searching users; sources of the required information; subjects needed, and the relationship of the user with the library material searched. Data were analyzed descriptively. The result of the study showed the dominant user searching for information was the researcher; source of information required was documentation, and subject/commodity needed by the user which was medicinal plants. There is a correlation between the researcher’s decision and the searching of journal literature and documentation; student decisions by searching books, journals, and documentation; as well as the general/private user’s decisions with book search and documentation. The information retrieval service at the Balittro Library needs to be improved by linking the online search database with the Balittro website so it can increase the number of online collections.

Computing Maximized Effectiveness Distance for Recall-Based Metrics

Given an effectiveness metric $M(\cdot)$ , two ordered document rankings $X_1$ and $X_2$ generated by a score-based information retrieval activity, and relevance labels in regard to some subset (possibly empty) of the documents appearing in the two rankings, Tan and Clarke's Maximized Effectiveness Distance (MED) computes the greatest difference in metric score that can be achieved that is consistent with all provided information, crystallized via a set of relevance assignments to the unlabeled documents such that $|M(X_1)-M(X_2)|$ is maximized. The closer the maximized effectiveness distance is to zero, the more similar $X_1$ and $X_2$ can be considered to be from the point of view of the metric $M(\cdot)$ . Here, we consider issues that arise when Tan and Clarke's definitions are applied to recall-based metrics, notably normalized discounted cumulative gain (NDCG), and average precision (AP). In particular, we show that MED can be applied to NDCG without requiring an a priori assumption in regard to the total number of relevant documents; we also show that making such an assumption leads to different outcomes for both NDCG and average precision (AP) compared to when no such assumption is made.

Comparative Analysis of Data Mining Tools and Techniques for Information Retrieval

Background/Objectives: There are a lot of information retrieval techniques available for getting information from different kinds of sources. Main aim of this paper is to improve information retrieval activities to a higher level. Different methods for information retrieval have been studied and discussed. It involves use of Fuzzy Ontology Generation framework (FOGA) framework along with Formal Concept Analysis (FCA) based clustering and keyword matching approach. Hidden Markov Model has been used for retrieval of data from search engines in an intelligent and efficient way for correct identification and retrieval from the database. Classification algorithm has been used for detection of community and conversion of large community graph to sub community graph for its better study and usage. Findings: It has been found that fuzzy ontology generation framework can automatically generate the fuzzy ontology which is very hard and time consuming task otherwise. Clustering of data can be done using the technique of formal concept analysis along with keyword matching method. There is a large amount of data available under similar words but with different meanings. So there has been a lot of problem in retrieval of exact data as required in a very short amount of time. In this case Hidden Markov Model can be used which can find the non-observable or hidden stochastic process from the observable stochastic process. Application/Improvements: Generalized Expectation-Maximization algorithm used with Hidden Markov Model can find unknown parameters. By adding frequency tracking algorithm along with Hidden Markov Model, we can also track audible data from a large database. Community detection algorithm along with Informap and Bigclam algorithms used with Hidden Markov Model will increase the modularity of data. Its applications include use of information retrieval of different types of data in an extremely faster and efficient way.

Creating Information Retrieval Competence of Future Translators: An Integrative Approach

This article deals with information retrieval competence in translation teaching and shows its importance for optimizing work of the future interpreters and translators in the modern globalised labor market. The goal of the article is to provide the authors’ view on the didactic aspect of training information retrieval activity to the future interpreters and translators and present the course ‘Information Retrieval in the Work of a Translator’ developed by the group of authors in the Translation Studies Department at Volgograd State University, Russia, introduced into the educational process. The article gives a detailed view of the course and its structure showing and explaining the main aspects of the training process and the results obtained. The advantages of the course are discussed in respect with the necessity to form skills and abilities necessary for translation as well as developing individual abilities of the students. The article concludes by emphasizing the significance of the integration of the course ‘Information Retrieval in the Work of a Translator’ with the practical courses of translation and interpretation and seminars in the translation theory and methodology, which promotes creation of professional translation competence and expansion of the general existential competence of future interpreters and translators. DOI: 10.5901/mjss.2015.v6n6s5p78

GeTFIRST: ontology-based keyword search towards semantic disambiguation

Purpose – This paper aims to improve the semantic-disambiguation capability of an information-retrieval system by taking advantages of a well-crafted classification tree. The unstructured nature and sheer volume of information accessible over networks have made it drastically difficult for users to seek relevant information. Many information-retrieval methods have been developed to address this problem, and keyword-based approach is amongst the most common approach. Such an approach is often inadequate to cope with the conceptualization associated with user needs and contents. This brings about the problem of semantic ambiguation that refers to the disagreement in meaning of terms between involving parties of a communication due to polysemy, leading to increased complexity and lesser accuracy in information integration, migration, retrieval and other related activities. Design/methodology/approach – A novel ontology-based search approach, named GeTFIRST (short for Graph-embedded Tree Fostering Information Retrieval SysTem), is proposed to disambiguate keywords semantically. The contribution is twofold. First, a search strategy is proposed to prune irrelevant concepts for accuracy improvement using our Graph-embedded Tree (GeT)-based ontology. Second, a path-based ranking algorithm is proposed to incorporate and reward the content specificity. Findings – An empirical evaluation was performed on United States Patent And Trademark Office (USPTO) patent datasets to compare our approach with full-text patent search approaches. The results showed that GeTFIRST handled the ambiguous keywords with higher keyword-disambiguation accuracy than traditional search approaches. Originality/value – The search approach of this paper copes with the semantic ambiguation by using our proposed GeT-based ontology and a path-based ranking algorithm.

PROTOCOL: Access to Electricity for Improving Health, Education and Welfare in Low‐ and Middle‐Income Countries: A Systematic Review

PROTOCOL: Access to Electricity for Improving Health, Education and Welfare in Low‐ and Middle‐Income Countries: A Systematic Review

Students in the information environment: a study of educational and extracurricular activities

The development of the global world makes it necessary to conduct international studies of students' educational and extracurricular activities. This article describes several research directions pursued at Herzen State Pedagogical University of Russia (HSPU), Saint-Petersburg and University of Silesia (US), Poland as well as research directions and outcomes within the European IRNet Project (http://www.irnet.us.edu.pl). Firstly, a questionnaire as well as other research tools were developed, implemented and analysed in order to ascertain students' new educational strategies and educational needs. Secondly, in order to understand in what way young people are aware of the surrounding reality a number of online discussions were held with the students and the discourses were analysed. The questionnaire included several research directions: the specifics of students' communication activities in an electronic networked environment; the characteristics of information retrieval activities and the preferences in the choice of particular resources in the network; the attitude towards the information and communication network resources and services used in education, future professional work and self-education.

Spaces, Trees, and Colors

Document retrieval is one of the best-established information retrieval activities since the ’60s, pervading all search engines. Its aim is to obtain, from a collection of text documents, those most relevant to a pattern query. Current technology is mostly oriented to “natural language” text collections, where inverted indexes are the preferred solution. As successful as this paradigm has been, it fails to properly handle various East Asian languages and other scenarios where the “natural language” assumptions do not hold. Inthis survey, we cover the recent research in extending the document retrieval techniques to a broader class of sequence collections, which has applications in bioinformatics, data and web mining, chemoinformatics, software engineering, multimedia information retrieval, and many other fields. We focus on the algorithmic aspects of the techniques, uncovering a rich world of relations between document retrieval challenges and fundamental problems on trees, strings, range queries, discrete geometry, and other areas.